The LLVM Pass Framework is an important part of the LLVM system, because LLVM
passes are where most of the interesting parts of the compiler exist. Passes
perform the transformations and optimizations that make up the compiler, they
build the analysis results that are used by these transformations, and they
are, above all, a structuring technique for compiler code.

All LLVM passes are subclasses of the Pass class, which implement
functionality by overriding virtual methods inherited from Pass. Depending
on how your pass works, you should inherit from the ModulePass , CallGraphSCCPass, FunctionPass , or LoopPass, or RegionPass, or BasicBlockPass classes, which gives the system more
information about what your pass does, and how it can be combined with other
passes. One of the main features of the LLVM Pass Framework is that it
schedules passes to run in an efficient way based on the constraints that your
pass meets (which are indicated by which class they derive from).

We start by showing you how to construct a pass, everything from setting up the
code, to compiling, loading, and executing it. After the basics are down, more
advanced features are discussed.

Here we describe how to write the “hello world” of passes. The “Hello” pass is
designed to simply print out the name of non-external functions that exist in
the program being compiled. It does not modify the program at all, it just
inspects it. The source code and files for this pass are available in the LLVM
source tree in the lib/Transforms/Hello directory.

First, configure and build LLVM. Next, you need to create a new directory
somewhere in the LLVM source base. For this example, we’ll assume that you
made lib/Transforms/Hello. Finally, you must set up a build script
that will compile the source code for the new pass. To do this,
copy the following into CMakeLists.txt:

add_llvm_loadable_module(LLVMHelloHello.cppPLUGIN_TOOLopt)

and the following line into lib/Transforms/CMakeLists.txt:

add_subdirectory(Hello)

(Note that there is already a directory named Hello with a sample “Hello”
pass; you may play with it – in which case you don’t need to modify any
CMakeLists.txt files – or, if you want to create everything from scratch,
use another name.)

This build script specifies that Hello.cpp file in the current directory
is to be compiled and linked into a shared object $(LEVEL)/lib/LLVMHello.so that
can be dynamically loaded by the opt tool via its -load
option. If your operating system uses a suffix other than .so (such as
Windows or Mac OS X), the appropriate extension will be used.

Now that we have the build scripts set up, we just need to write the code for
the pass itself.

Which are needed because we are writing a Pass, we are operating on
Functions, and we will
be doing some printing.

Next we have:

usingnamespacellvm;

… which is required because the functions from the include files live in the
llvm namespace.

Next we have:

namespace{

… which starts out an anonymous namespace. Anonymous namespaces are to C++
what the “static” keyword is to C (at global scope). It makes the things
declared inside of the anonymous namespace visible only to the current file.
If you’re not familiar with them, consult a decent C++ book for more
information.

Next, we declare our pass itself:

structHello:publicFunctionPass{

This declares a “Hello” class that is a subclass of FunctionPass. The different builtin pass subclasses
are described in detail later, but
for now, know that FunctionPass operates on a function at a time.

staticcharID;Hello():FunctionPass(ID){}

This declares pass identifier used by LLVM to identify pass. This allows LLVM
to avoid using expensive C++ runtime information.

boolrunOnFunction(Function&F)override{errs()<<"Hello: ";errs().write_escaped(F.getName())<<'\n';returnfalse;}};// end of struct Hello}// end of anonymous namespace

We declare a runOnFunction method,
which overrides an abstract virtual method inherited from FunctionPass. This is where we are supposed to do our
thing, so we just print out our message with the name of each function.

charHello::ID=0;

We initialize pass ID here. LLVM uses ID’s address to identify a pass, so
initialization value is not important.

Lastly, we register our classHello, giving it a command line argument “hello”, and a name “Hello
World Pass”. The last two arguments describe its behavior: if a pass walks CFG
without modifying it then the third argument is set to true; if a pass is
an analysis pass, for example dominator tree pass, then true is supplied as
the fourth argument.

As a whole, the .cpp file looks like:

#include"llvm/Pass.h"#include"llvm/IR/Function.h"#include"llvm/Support/raw_ostream.h"usingnamespacellvm;namespace{structHello:publicFunctionPass{staticcharID;Hello():FunctionPass(ID){}boolrunOnFunction(Function&F)override{errs()<<"Hello: ";errs().write_escaped(F.getName())<<'\n';returnfalse;}};// end of struct Hello}// end of anonymous namespacecharHello::ID=0;staticRegisterPass<Hello>X("hello","Hello World Pass",false/* Only looks at CFG */,false/* Analysis Pass */);

Now that it’s all together, compile the file with a simple “gmake” command
from the top level of your build directory and you should get a new file
“lib/LLVMHello.so”. Note that everything in this file is
contained in an anonymous namespace — this reflects the fact that passes
are self contained units that do not need external interfaces (although they
can have them) to be useful.

Now that you have a brand new shiny shared object file, we can use the
opt command to run an LLVM program through your pass. Because you
registered your pass with RegisterPass, you will be able to use the
opt tool to access it, once loaded.

To test it, follow the example at the end of the Getting Started with the LLVM System to
compile “Hello World” to LLVM. We can now run the bitcode file (hello.bc) for
the program through our transformation like this (or course, any bitcode file
will work):

The -load option specifies that opt should load your pass
as a shared object, which makes “-hello” a valid command line argument
(which is one reason you need to register your pass). Because the Hello pass does not modify
the program in any interesting way, we just throw away the result of
opt (sending it to /dev/null).

To see what happened to the other string you registered, try running
opt with the -help option:

The pass name gets added as the information string for your pass, giving some
documentation to users of opt. Now that you have a working pass,
you would go ahead and make it do the cool transformations you want. Once you
get it all working and tested, it may become useful to find out how fast your
pass is. The PassManager provides a
nice command line option (--time-passes) that allows you to get
information about the execution time of your pass along with the other passes
you queue up. For example:

As you can see, our implementation above is pretty fast. The additional
passes listed are automatically inserted by the opt tool to verify
that the LLVM emitted by your pass is still valid and well formed LLVM, which
hasn’t been broken somehow.

Now that you have seen the basics of the mechanics behind passes, we can talk
about some more details of how they work and how to use them.

One of the first things that you should do when designing a new pass is to
decide what class you should subclass for your pass. The Hello World example uses the FunctionPass class for its implementation, but we did
not discuss why or when this should occur. Here we talk about the classes
available, from the most general to the most specific.

When choosing a superclass for your Pass, you should choose the most
specific class possible, while still being able to meet the requirements
listed. This gives the LLVM Pass Infrastructure information necessary to
optimize how passes are run, so that the resultant compiler isn’t unnecessarily
slow.

The most plain and boring type of pass is the “ImmutablePass” class. This pass
type is used for passes that do not have to be run, do not change state, and
never need to be updated. This is not a normal type of transformation or
analysis, but can provide information about the current compiler configuration.

Although this pass class is very infrequently used, it is important for
providing information about the current target machine being compiled for, and
other static information that can affect the various transformations.

ImmutablePasses never invalidate other transformations, are never
invalidated, and are never “run”.

The ModulePass class
is the most general of all superclasses that you can use. Deriving from
ModulePass indicates that your pass uses the entire program as a unit,
referring to function bodies in no predictable order, or adding and removing
functions. Because nothing is known about the behavior of ModulePass
subclasses, no optimization can be done for their execution.

A module pass can use function level passes (e.g. dominators) using the
getAnalysis interface getAnalysis<DominatorTree>(llvm::Function*) to
provide the function to retrieve analysis result for, if the function pass does
not require any module or immutable passes. Note that this can only be done
for functions for which the analysis ran, e.g. in the case of dominators you
should only ask for the DominatorTree for function definitions, not
declarations.

To write a correct ModulePass subclass, derive from ModulePass and
overload the runOnModule method with the following signature:

The CallGraphSCCPass is used by
passes that need to traverse the program bottom-up on the call graph (callees
before callers). Deriving from CallGraphSCCPass provides some mechanics
for building and traversing the CallGraph, but also allows the system to
optimize execution of CallGraphSCCPasses. If your pass meets the
requirements outlined below, and doesn’t meet the requirements of a
FunctionPass or BasicBlockPass, you should derive from
CallGraphSCCPass.

TODO: explain briefly what SCC, Tarjan’s algo, and B-U mean.

To be explicit, CallGraphSCCPass subclasses are:

… not allowed to inspect or modify any Functions other than those
in the current SCC and the direct callers and direct callees of the SCC.

… required to preserve the current CallGraph object, updating it to
reflect any changes made to the program.

… not allowed to add or remove SCC’s from the current Module, though
they may change the contents of an SCC.

… allowed to add or remove global variables from the current Module.

… allowed to maintain state across invocations of runOnSCC (including global data).

Implementing a CallGraphSCCPass is slightly tricky in some cases because it
has to handle SCCs with more than one node in it. All of the virtual methods
described below should return true if they modified the program, or
false if they didn’t.

The doInitialization method is allowed to do most of the things that
CallGraphSCCPasses are not allowed to do. They can add and remove
functions, get pointers to functions, etc. The doInitialization method is
designed to do simple initialization type of stuff that does not depend on the
SCCs being processed. The doInitialization method call is not scheduled to
overlap with any other pass executions (thus it should be very fast).

In contrast to ModulePass subclasses, FunctionPass subclasses do have a
predictable, local behavior that can be expected by the system. All
FunctionPass execute on each function in the program independent of all of
the other functions in the program. FunctionPasses do not require that
they are executed in a particular order, and FunctionPasses do not modify
external functions.

To be explicit, FunctionPass subclasses are not allowed to:

Inspect or modify a Function other than the one currently being processed.

Add or remove Functions from the current Module.

Add or remove global variables from the current Module.

Maintain state across invocations of runOnFunction (including global data).

Implementing a FunctionPass is usually straightforward (See the Hello
World pass for example).
FunctionPasses may overload three virtual methods to do their work. All
of these methods should return true if they modified the program, or
false if they didn’t.

The doInitialization method is allowed to do most of the things that
FunctionPasses are not allowed to do. They can add and remove functions,
get pointers to functions, etc. The doInitialization method is designed to
do simple initialization type of stuff that does not depend on the functions
being processed. The doInitialization method call is not scheduled to
overlap with any other pass executions (thus it should be very fast).

A good example of how this method should be used is the LowerAllocations pass. This pass
converts malloc and free instructions into platform dependent
malloc() and free() function calls. It uses the doInitialization
method to get a reference to the malloc and free functions that it
needs, adding prototypes to the module if necessary.

All LoopPass execute on each loop in the function independent of all of the
other loops in the function. LoopPass processes loops in loop nest order
such that outer most loop is processed last.

LoopPass subclasses are allowed to update loop nest using LPPassManager
interface. Implementing a loop pass is usually straightforward.
LoopPasses may overload three virtual methods to do their work. All
these methods should return true if they modified the program, or false
if they didn’t.

A LoopPass subclass which is intended to run as part of the main loop pass
pipeline needs to preserve all of the same function analyses that the other
loop passes in its pipeline require. To make that easier,
a getLoopAnalysisUsage function is provided by LoopUtils.h. It can be
called within the subclass’s getAnalysisUsage override to get consistent
and correct behavior. Analogously, INITIALIZE_PASS_DEPENDENCY(LoopPass)
will initialize this set of function analyses.

The doInitialization method is designed to do simple initialization type of
stuff that does not depend on the functions being processed. The
doInitialization method call is not scheduled to overlap with any other
pass executions (thus it should be very fast). LPPassManager interface
should be used to access Function or Module level analysis information.

The runOnLoop method must be implemented by your subclass to do the
transformation or analysis work of your pass. As usual, a true value
should be returned if the function is modified. LPPassManager interface
should be used to update loop nest.

RegionPass is similar to LoopPass,
but executes on each single entry single exit region in the function.
RegionPass processes regions in nested order such that the outer most
region is processed last.

RegionPass subclasses are allowed to update the region tree by using the
RGPassManager interface. You may overload three virtual methods of
RegionPass to implement your own region pass. All these methods should
return true if they modified the program, or false if they did not.

The doInitialization method is designed to do simple initialization type of
stuff that does not depend on the functions being processed. The
doInitialization method call is not scheduled to overlap with any other
pass executions (thus it should be very fast). RPPassManager interface
should be used to access Function or Module level analysis information.

The runOnRegion method must be implemented by your subclass to do the
transformation or analysis work of your pass. As usual, a true value should be
returned if the region is modified. RGPassManager interface should be used to
update region tree.

BasicBlockPasses are just like FunctionPass’s , except that they must limit their scope
of inspection and modification to a single basic block at a time. As such,
they are not allowed to do any of the following:

The doInitialization method is allowed to do most of the things that
BasicBlockPasses are not allowed to do, but that FunctionPasses
can. The doInitialization method is designed to do simple initialization
that does not depend on the BasicBlocks being processed. The
doInitialization method call is not scheduled to overlap with any other
pass executions (thus it should be very fast).

Override this function to do the work of the BasicBlockPass. This function
is not allowed to inspect or modify basic blocks other than the parameter, and
are not allowed to modify the CFG. A true value must be returned if the
basic block is modified.

The doFinalization method is an infrequently used method that is called
when the pass framework has finished calling runOnBasicBlock for every BasicBlock in the program
being compiled. This can be used to perform per-function finalization.

A MachineFunctionPass is a part of the LLVM code generator that executes on
the machine-dependent representation of each LLVM function in the program.

Code generator passes are registered and initialized specially by
TargetMachine::addPassesToEmitFile and similar routines, so they cannot
generally be run from the opt or bugpoint commands.

A MachineFunctionPass is also a FunctionPass, so all the restrictions
that apply to a FunctionPass also apply to it. MachineFunctionPasses
also have additional restrictions. In particular, MachineFunctionPasses
are not allowed to do any of the following:

runOnMachineFunction can be considered the main entry point of a
MachineFunctionPass; that is, you should override this method to do the
work of your MachineFunctionPass.

The runOnMachineFunction method is called on every MachineFunction in a
Module, so that the MachineFunctionPass may perform optimizations on
the machine-dependent representation of the function. If you want to get at
the LLVM Function for the MachineFunction you’re working on, use
MachineFunction’s getFunction() accessor method — but remember, you
may not modify the LLVM Function or its contents from a
MachineFunctionPass.

In the Hello World example pass we
illustrated how pass registration works, and discussed some of the reasons that
it is used and what it does. Here we discuss how and why passes are
registered.

As we saw above, passes are registered with the RegisterPass template. The
template parameter is the name of the pass that is to be used on the command
line to specify that the pass should be added to a program (for example, with
opt or bugpoint). The first argument is the name of the
pass, which is to be used for the -help output of programs, as well
as for debug output generated by the –debug-pass option.

If you want your pass to be easily dumpable, you should implement the virtual
print method:

The print method must be implemented by “analyses” in order to print a
human readable version of the analysis results. This is useful for debugging
an analysis itself, as well as for other people to figure out how an analysis
works. Use the opt -analyze argument to invoke this method.

The llvm::raw_ostream parameter specifies the stream to write the results
on, and the Module parameter gives a pointer to the top level module of the
program that has been analyzed. Note however that this pointer may be NULL
in certain circumstances (such as calling the Pass::dump() from a
debugger), so it should only be used to enhance debug output, it should not be
depended on.

One of the main responsibilities of the PassManager is to make sure that
passes interact with each other correctly. Because PassManager tries to
optimize the execution of passes it
must know how the passes interact with each other and what dependencies exist
between the various passes. To track this, each pass can declare the set of
passes that are required to be executed before the current pass, and the passes
which are invalidated by the current pass.

Typically this functionality is used to require that analysis results are
computed before your pass is run. Running arbitrary transformation passes can
invalidate the computed analysis results, which is what the invalidation set
specifies. If a pass does not implement the getAnalysisUsage method, it defaults to not having any
prerequisite passes, and invalidating all other passes.

By implementing the getAnalysisUsage method, the required and invalidated
sets may be specified for your transformation. The implementation should fill
in the AnalysisUsage object with
information about which passes are required and not invalidated. To do this, a
pass may call any of the following methods on the AnalysisUsage object:

If your pass requires a previous pass to be executed (an analysis for example),
it can use one of these methods to arrange for it to be run before your pass.
LLVM has many different types of analyses and passes that can be required,
spanning the range from DominatorSet to BreakCriticalEdges. Requiring
BreakCriticalEdges, for example, guarantees that there will be no critical
edges in the CFG when your pass has been run.

Some analyses chain to other analyses to do their job. For example, an
AliasAnalysis <AliasAnalysis> implementation is required to chain to other alias analysis passes. In cases where
analyses chain, the addRequiredTransitive method should be used instead of
the addRequired method. This informs the PassManager that the
transitively required pass should be alive as long as the requiring pass is.

One of the jobs of the PassManager is to optimize how and when analyses are
run. In particular, it attempts to avoid recomputing data unless it needs to.
For this reason, passes are allowed to declare that they preserve (i.e., they
don’t invalidate) an existing analysis if it’s available. For example, a
simple constant folding pass would not modify the CFG, so it can’t possibly
affect the results of dominator analysis. By default, all passes are assumed
to invalidate all others.

The AnalysisUsage class provides several methods which are useful in
certain circumstances that are related to addPreserved. In particular, the
setPreservesAll method can be called to indicate that the pass does not
modify the LLVM program at all (which is true for analyses), and the
setPreservesCFG method can be used by transformations that change
instructions in the program but do not modify the CFG or terminator
instructions (note that this property is implicitly set for
BasicBlockPasses).

addPreserved is particularly useful for transformations like
BreakCriticalEdges. This pass knows how to update a small set of loop and
dominator related analyses if they exist, so it can preserve them, despite the
fact that it hacks on the CFG.

The Pass::getAnalysis<> method is automatically inherited by your class,
providing you with access to the passes that you declared that you required
with the getAnalysisUsage
method. It takes a single template argument that specifies which pass class
you want, and returns a reference to that pass. For example:

This method call returns a reference to the pass desired. You may get a
runtime assertion failure if you attempt to get an analysis that you did not
declare as required in your getAnalysisUsage implementation. This method can be
called by your run* method implementation, or by any other local method
invoked by your run* method.

A module level pass can use function level analysis info using this interface.
For example:

In above example, runOnFunction for DominatorTree is called by pass
manager before returning a reference to the desired pass.

If your pass is capable of updating analyses if they exist (e.g.,
BreakCriticalEdges, as described above), you can use the
getAnalysisIfAvailable method, which returns a pointer to the analysis if
it is active. For example:

if(DominatorSet*DS=getAnalysisIfAvailable<DominatorSet>()){// A DominatorSet is active. This code will update it.}

Now that we understand the basics of how passes are defined, how they are used,
and how they are required from other passes, it’s time to get a little bit
fancier. All of the pass relationships that we have seen so far are very
simple: one pass depends on one other specific pass to be run before it can
run. For many applications, this is great, for others, more flexibility is
required.

In particular, some analyses are defined such that there is a single simple
interface to the analysis results, but multiple ways of calculating them.
Consider alias analysis for example. The most trivial alias analysis returns
“may alias” for any alias query. The most sophisticated analysis a
flow-sensitive, context-sensitive interprocedural analysis that can take a
significant amount of time to execute (and obviously, there is a lot of room
between these two extremes for other implementations). To cleanly support
situations like this, the LLVM Pass Infrastructure supports the notion of
Analysis Groups.

An Analysis Group is a single simple interface that may be implemented by
multiple different passes. Analysis Groups can be given human readable names
just like passes, but unlike passes, they need not derive from the Pass
class. An analysis group may have one or more implementations, one of which is
the “default” implementation.

Analysis groups are used by client passes just like other passes are: the
AnalysisUsage::addRequired() and Pass::getAnalysis() methods. In order
to resolve this requirement, the PassManager scans the available passes to see if any
implementations of the analysis group are available. If none is available, the
default implementation is created for the pass to use. All standard rules for
interaction between passes still
apply.

Although Pass Registration is
optional for normal passes, all analysis group implementations must be
registered, and must use the INITIALIZE_AG_PASS template to join the
implementation pool. Also, a default implementation of the interface must
be registered with RegisterAnalysisGroup.

As a concrete example of an Analysis Group in action, consider the
AliasAnalysis
analysis group. The default implementation of the alias analysis interface
(the basicaa pass)
just does a few simple checks that don’t require significant analysis to
compute (such as: two different globals can never alias each other, etc).
Passes that use the AliasAnalysis interface (for
example the gvn pass), do not
care which implementation of alias analysis is actually provided, they just use
the designated interface.

From the user’s perspective, commands work just like normal. Issuing the
command opt-gvn... will cause the basicaa class to be instantiated
and added to the pass sequence. Issuing the command opt-somefancyaa-gvn... will cause the gvn pass to use the somefancyaa alias analysis
(which doesn’t actually exist, it’s just a hypothetical example) instead.

The RegisterAnalysisGroup template is used to register the analysis group
itself, while the INITIALIZE_AG_PASS is used to add pass implementations to
the analysis group. First, an analysis group should be registered, with a
human readable name provided for it. Unlike registration of passes, there is
no command line argument to be specified for the Analysis Group Interface
itself, because it is “abstract”:

staticRegisterAnalysisGroup<AliasAnalysis>A("Alias Analysis");

Once the analysis is registered, passes can declare that they are valid
implementations of the interface by using the following code:

namespace{// Declare that we implement the AliasAnalysis interfaceINITIALIZE_AG_PASS(FancyAA,AliasAnalysis,"somefancyaa","A more complex alias analysis implementation",false,// Is CFG Only?true,// Is Analysis?false);// Is default Analysis Group implementation?}

This just shows a class FancyAA that uses the INITIALIZE_AG_PASS macro
both to register and to “join” the AliasAnalysis analysis group.
Every implementation of an analysis group should join using this macro.

namespace{// Declare that we implement the AliasAnalysis interfaceINITIALIZE_AG_PASS(BasicAA,AliasAnalysis,"basicaa","Basic Alias Analysis (default AA impl)",false,// Is CFG Only?true,// Is Analysis?true);// Is default Analysis Group implementation?}

Here we show how the default implementation is specified (using the final
argument to the INITIALIZE_AG_PASS template). There must be exactly one
default implementation available at all times for an Analysis Group to be used.
Only default implementation can derive from ImmutablePass. Here we declare
that the BasicAliasAnalysis pass is the default
implementation for the interface.

The Statistic class is
designed to be an easy way to expose various success metrics from passes.
These statistics are printed at the end of a run, when the -stats
command line option is enabled on the command line. See the Statistics
section in the Programmer’s Manual for details.

The PassManagerclass takes a list of
passes, ensures their prerequisites
are set up correctly, and then schedules passes to run efficiently. All of the
LLVM tools that run passes use the PassManager for execution of these passes.

The PassManager does two main things to try to reduce the execution time of a
series of passes:

Share analysis results. The PassManager attempts to avoid
recomputing analysis results as much as possible. This means keeping track
of which analyses are available already, which analyses get invalidated, and
which analyses are needed to be run for a pass. An important part of work
is that the PassManager tracks the exact lifetime of all analysis
results, allowing it to free memory allocated to holding analysis results
as soon as they are no longer needed.

Pipeline the execution of passes on the program. The PassManager
attempts to get better cache and memory usage behavior out of a series of
passes by pipelining the passes together. This means that, given a series
of consecutive FunctionPass, it
will execute all of the FunctionPass on the first function, then all of the
FunctionPasses on the second
function, etc… until the entire program has been run through the passes.

This improves the cache behavior of the compiler, because it is only
touching the LLVM program representation for a single function at a time,
instead of traversing the entire program. It reduces the memory consumption
of compiler, because, for example, only one DominatorSet needs to be
calculated at a time. This also makes it possible to implement some
interesting enhancements in the future.

The effectiveness of the PassManager is influenced directly by how much
information it has about the behaviors of the passes it is scheduling. For
example, the “preserved” set is intentionally conservative in the face of an
unimplemented getAnalysisUsage
method. Not implementing when it should be implemented will have the effect of
not allowing any analysis results to live across the execution of your pass.

The PassManager class exposes a --debug-pass command line options that
is useful for debugging pass execution, seeing how things work, and diagnosing
when you should be preserving more analyses than you currently are. (To get
information about all of the variants of the --debug-pass option, just type
“opt-help-hidden”).

By using the –debug-pass=Structure option, for example, we can see how our
Hello World pass interacts with other
passes. Lets try it out with the gvn and licm passes:

This output shows us when passes are constructed.
Here we see that GVN uses dominator tree information to do its job. The LICM pass
uses natural loop information, which uses dominator tree as well.

After the LICM pass, the module verifier runs (which is automatically added by
the opt tool), which uses the dominator tree to check that the
resultant LLVM code is well formed. Note that the dominator tree is computed
once, and shared by three passes.

Lets see how this changes when we run the Hello World pass in between the two passes:

The PassManager automatically determines when to compute analysis results,
and how long to keep them around for. Because the lifetime of the pass object
itself is effectively the entire duration of the compilation process, we need
some way to free analysis results when they are no longer useful. The
releaseMemory virtual method is the way to do this.

If you are writing an analysis or any other pass that retains a significant
amount of state (for use by another pass which “requires” your pass and uses
the getAnalysis method) you should
implement releaseMemory to, well, release the memory allocated to maintain
this internal state. This method is called after the run* method for the
class, before the next call of run* in your pass.

Size matters when constructing production quality tools using LLVM, both for
the purposes of distribution, and for regulating the resident code size when
running on the target system. Therefore, it becomes desirable to selectively
use some passes, while omitting others and maintain the flexibility to change
configurations later on. You want to be able to do all this, and, provide
feedback to the user. This is where pass registration comes into play.

The fundamental mechanisms for pass registration are the
MachinePassRegistry class and subclasses of MachinePassRegistryNode.

An instance of MachinePassRegistry is used to maintain a list of
MachinePassRegistryNode objects. This instance maintains the list and
communicates additions and deletions to the command line interface.

An instance of MachinePassRegistryNode subclass is used to maintain
information provided about a particular pass. This information includes the
command line name, the command help string and the address of the function used
to create an instance of the pass. A global static constructor of one of these
instances registers with a corresponding MachinePassRegistry, the static
destructor unregisters. Thus a pass that is statically linked in the tool
will be registered at start up. A dynamically loaded pass will register on
load and unregister at unload.

There are predefined registries to track instruction scheduling
(RegisterScheduler) and register allocation (RegisterRegAlloc) machine
passes. Here we will describe how to register a register allocator machine
pass.

And that’s it. The user is now free to use -regalloc=myregalloc as an
option. Registering instruction schedulers is similar except use the
RegisterScheduler class. Note that the
RegisterScheduler::FunctionPassCtor is significantly different from
RegisterRegAlloc::FunctionPassCtor.

To force the load/linking of your register allocator into the
llc/lli tools, add your creator function’s global
declaration to Passes.h and add a “pseudo” call line to
llvm/Codegen/LinkAllCodegenComponents.h.

Unfortunately, using GDB with dynamically loaded passes is not as easy as it
should be. First of all, you can’t set a breakpoint in a shared object that
has not been loaded yet, and second of all there are problems with inlined
functions in shared objects. Here are some suggestions to debugging your pass
with GDB.

For sake of discussion, I’m going to assume that you are debugging a
transformation invoked by opt, although nothing described here
depends on that.

$ gdb opt
GNU gdb 5.0Copyright 2000 Free Software Foundation, Inc.GDB is free software, covered by the GNU General Public License, and you arewelcome to change it and/or distribute copies of it under certain conditions.Type "show copying" to see the conditions.There is absolutely no warranty for GDB. Type "show warranty" for details.This GDB was configured as "sparc-sun-solaris2.6"...(gdb)

Note that opt has a lot of debugging information in it, so it takes
time to load. Be patient. Since we cannot set a breakpoint in our pass yet
(the shared object isn’t loaded until runtime), we must execute the process,
and have it stop before it invokes our pass, but after it has loaded the shared
object. The most foolproof way of doing this is to set a breakpoint in
PassManager::run and then run the process with the arguments you want:

Once you have the basics down, there are a couple of problems that GDB has,
some with solutions, some without.

Inline functions have bogus stack information. In general, GDB does a pretty
good job getting stack traces and stepping through inline functions. When a
pass is dynamically loaded however, it somehow completely loses this
capability. The only solution I know of is to de-inline a function (move it
from the body of a class to a .cpp file).

Restarting the program breaks breakpoints. After following the information
above, you have succeeded in getting some breakpoints planted in your pass.
Next thing you know, you restart the program (i.e., you type “run” again),
and you start getting errors about breakpoints being unsettable. The only
way I have found to “fix” this problem is to delete the breakpoints that are
already set in your pass, run the program, and re-set the breakpoints once
execution stops in PassManager::run.

Hopefully these tips will help with common case debugging situations. If you’d
like to contribute some tips of your own, just contact Chris.

Multiple CPU machines are becoming more common and compilation can never be
fast enough: obviously we should allow for a multithreaded compiler. Because
of the semantics defined for passes above (specifically they cannot maintain
state across invocations of their run* methods), a nice clean way to
implement a multithreaded compiler would be for the PassManager class to
create multiple instances of each pass object, and allow the separate instances
to be hacking on different parts of the program at the same time.

This implementation would prevent each of the passes from having to implement
multithreaded constructs, requiring only the LLVM core to have locking in a few
places (for global resources). Although this is a simple extension, we simply
haven’t had time (or multiprocessor machines, thus a reason) to implement this.
Despite that, we have kept the LLVM passes SMP ready, and you should too.